Hydraulic engineering safety risk evaluation method and system

Abstract

The invention discloses a hydraulic engineering safety risk evaluation method and system, and particularly relates to the technical field of hydraulic engineering. Whether abnormal stress concentration or release exists or not is judged by analyzing the change rate fluctuation condition of crustal stress along with time, if abnormity is detected, an array type earthquake monitoring sensor is adopted to analyze micro-earthquake characteristics and earthquake wave speed abnormity of a dam area, whether local rock mass structure change or hidden damage exists or not is judged, and a geological disaster interference evaluation model is constructed. Calculating an interference index by integrating a crustal stress fluctuation index and a seismic wave speed anomaly index, when the interference index reaches a high interference degree, immediately starting a dynamic adjustment mechanism by the system, remotely adjusting the sensitivity of monitoring equipment and the data acquisition frequency according to the interference condition, and automatically optimizing an early warning threshold value; interference of geological disasters on monitoring equipment can be effectively reduced, the accuracy of hydraulic engineering safety monitoring is improved, real-time early warning and intelligent regulation and control are achieved, and the dam safety management capacity is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of water conservancy projects, and in particular to a water conservancy project safety risk assessment method and system. Background Art

[0002] Water conservancy project safety risk assessment refers to the identification, evaluation and control of possible safety risks in the planning, design, construction and operation of water conservancy projects through systematic analysis and scientific methods. This assessment usually covers multiple aspects such as structural stability, flood risk, geological disasters, construction safety, operation and maintenance, etc., and adopts a combination of qualitative and quantitative methods, such as risk matrix, analytic hierarchy process (AHP), fuzzy comprehensive evaluation method, etc., to ensure project safety and reduce accidents.

[0003] At present, the reservoir dam safety monitoring system is an important technical means for the safety risk assessment of water conservancy projects. For example, the reservoir dam monitoring technology based on the Internet of Things and big data analysis can collect data such as dam deformation, seepage, stress and strain in real time, and conduct risk warning through artificial intelligence algorithms. For example, the Three Gorges Dam Safety Monitoring System uses satellite remote sensing, automated monitoring sensors and other technologies to conduct all-weather monitoring and safety assessment of the dam's operating conditions, effectively improving the level of project safety management.

[0004] The prior art has the following deficiencies: Some dams are built in areas with complex terrain, such as mountains and canyons. Their foundations and surrounding rock and soil structures are greatly affected by geological conditions, and there may be risks such as landslides, subsidence, ground fissures, and rock collapse. For example, under the action of heavy rain or earthquakes, landslides may occur in the mountains upstream or on both sides of the dam, causing the sensor base to shift, the monitoring equipment to be buried or damaged, and the monitoring data to be distorted or even interrupted. At the same time, foundation settlement may cause deformation of the dam structure and affect the measurement accuracy of the monitoring system. In addition, if geological disasters distort the data of monitoring equipment, it may affect the reliability of dam safety monitoring and the accuracy of early warning. Summary of the invention

[0005] The purpose of the present invention is to provide a water conservancy project safety risk assessment method and system to address the deficiencies in the background technology.

[0006] In order to achieve the above object, the present invention provides the following technical solution: a method for evaluating the safety risk of a water conservancy project, comprising the following steps: S1: Monitor the stress changes of the dam foundation and surrounding rock formations through borehole stress gauges, analyze the fluctuation of the rate of change of ground stress over time, and determine whether there is abnormal stress concentration or release; S2: If there is abnormal stress concentration or release, the array-type seismic monitoring sensor will be used to analyze the abnormal changes in seismic wave velocity based on the propagation characteristics of microseisms and seismic waves in the dam area to determine whether there are local rock structure changes or hidden damage; S3: Construct a geological disaster interference assessment model, calculate the interference index according to the fluctuation of the change rate of ground stress over time and the abnormal change of seismic wave velocity, and divide the interference degree into high interference degree level and low interference degree level; S4: When the interference index reaches a high interference level, the dynamic adjustment mechanism is immediately activated to remotely adjust the sensitivity and data collection frequency of the monitoring equipment according to the interference situation, and automatically adjust the warning threshold to increase or decrease the warning sensitivity.

[0007] Preferably, in S1, the fluctuation of the rate of change of the ground stress over time is analyzed to generate a ground stress change rate fluctuation index, and the method for obtaining the ground stress change rate fluctuation index is: Collect the time series of the rate of change of ground stress , the expression is: ;in: is the change of ground stress, Δt is the time interval, and the ground stress change rate series Decompose into multiple component IMFs of different scales, decompose the original signal by the envelope method, and extract multiple intrinsic mode functions: ;in: is the ith IMF component, is the final residual, N represents the number of intrinsic mode functions obtained by decomposition, that is, the number of intrinsic mode functions extracted from the original signal during the decomposition process, and the termination condition is set. Stop decomposition when it becomes a monotonic function or a low-frequency trend signal; Calculate the energy contribution of each IMF component : ; Calculate the instantaneous amplitude and instantaneous frequency of each IMF component, analyze the fluctuation characteristics of the ground stress change rate, and Perform Hilbert transform to obtain its analytical signal and calculate the instantaneous amplitude , the expression is: ; is the analytical signal obtained after Hilbert transform; calculate the weighted average instantaneous amplitude , the expression is: ;in: is the energy weight, M is the total instantaneous amplitude, and the weighted average instantaneous frequency is calculated , the expression is: ; In the formula, is the instantaneous frequency, and the calculation expression is: ; Calculate the stress change rate fluctuation index SCRFI, and the expression is: .

[0008] Preferably, set the normal range [SCRFImin, SCRFImax] for early warning: Low risk: SCRFI ≤ SCRFImin; Medium risk: SCRFImin < SCRFI ≤ SCRFImax; High risk: SCRFI > SCRFImax. At this time, there is stress concentration or release, and an early warning signal is generated.

[0009] Preferably, after analyzing the abnormal change of seismic wave velocity, generate the seismic wave velocity anomaly index. The acquisition method of the seismic wave velocity anomaly index is: Set the seismic wave velocity time series as: ; where: V(k) is the seismic wave velocity at the k-th moment, construct the accumulated generating sequence, and perform the first-order accumulated generating: ; where: ; Use the GM(1,1) model to set that the accumulated generating sequence satisfies the differential equation: ; where: a is the development coefficient, indicating the change trend of seismic wave velocity; b is the grey action quantity, indicating the external influence of the system. Use the least squares method to estimate a and b. Based on the solved a and b, obtain the prediction formula of the GM(1,1) model: ; Through the first-order inverse accumulation generation, obtain the predicted value of the original sequence , and the expression is: ; Define the seismic wave velocity anomaly index SWVAI, and the expression is: ; where: represents the actual observed seismic wave velocity at the k-th moment, represents the seismic wave velocity predicted by the GM(1,1) model, is the standard deviation of historical prediction errors, and ϵ is the smoothing factor.

[0010] Preferably, judge the rock mass structure state according to the SWVAI value: SWVAI < 1 indicates that the rock mass state is normal and there is no significant anomaly in seismic wave velocity; 1 ≤ SWVAI < 2 indicates that the rock mass state is slightly abnormal and there is local crack development; 2 ≤ SWVAI < 3 indicates that the rock mass state is moderately abnormal and there is rock mass rupture or increased water infiltration; SWVAI ≥ 3 indicates that the rock mass state is highly abnormal and there is large-scale rock mass rupture, landslide or dam foundation instability; when SWVAI ≥ 3, trigger an automatic early warning, increase the monitoring frequency, and collect seismic wave velocity data with a higher density.

[0011] Preferably, in S3, a geological disaster interference assessment model is constructed, and an interference index is calculated according to the fluctuation of the change rate of ground stress over time and the abnormal change of seismic wave velocity, and the interference degree is divided into a high interference degree level and a low interference degree level; The in-situ stress change rate fluctuation index and the seismic wave velocity anomaly index are normalized so that they are both between [0, 1]. The interference index is obtained by weighted average calculation of the normalized in-situ stress change rate fluctuation index and seismic wave velocity anomaly index.

[0012] Preferably, the obtained interference index is compared with the interference index reference threshold value pre-set according to historical data. If the interference index is greater than or equal to the pre-set interference index reference threshold value, it means that there is significant geostress anomaly or rock structure damage in the dam area, and the monitoring data is seriously interfered with, requiring further analysis and early warning, and the interference degree is classified as a high interference level; if the interference index is less than the pre-set interference index reference threshold value, it means that the rock structure in the dam area is stable, the geostress and seismic wave velocity changes are within the normal range, and the monitoring data is less interfered with, and the interference degree is classified as a low interference level.

[0013] Preferably, in S4, when the interference index reaches a high interference level, the dynamic adjustment mechanism is immediately started to remotely adjust the sensitivity and data acquisition frequency of the monitoring equipment according to the interference situation, and automatically adjust the warning threshold to increase or decrease the warning sensitivity; When the interference index reaches a high interference level, that is, the interference index is greater than or equal to the preset interference index reference threshold, the dynamic adjustment mechanism is immediately activated to analyze all interference index data within a fixed time period, calculate the mean and standard deviation of the interference index, and determine the interference situation; If the interference index mean is greater than or equal to the reference threshold of the interference index mean, and the interference index standard deviation is less than the reference threshold of the interference index standard deviation, it means that the situation is stable and high interference is needed. It is necessary to enhance the sensitivity of the equipment, increase the frequency of data collection, reduce the warning threshold, and improve the warning sensitivity. If the interference index mean is greater than or equal to the reference threshold of the interference index mean, and the interference index standard deviation is greater than or equal to the reference threshold of the interference index standard deviation, it indicates that this is a high-interference situation with volatility, and the data collection frequency needs to be increased to keep the warning threshold unchanged; If the interference index mean is less than the reference threshold of the interference index mean, and the interference index standard deviation is greater than or equal to the reference threshold of the interference index standard deviation, it indicates that this is a short-term abnormal fluctuation. Increase the data collection frequency, do not adjust the warning threshold for the time being, and continue monitoring; If the interference index mean is less than the reference threshold of the interference index mean, and the interference index standard deviation is less than the reference threshold of the interference index standard deviation, it indicates that the interference situation is low and the current monitoring strategy is maintained without adjustment.

[0014] The present invention also provides a water conservancy project safety risk assessment system, including a ground stress monitoring module, a seismic wave monitoring and analysis module, a geological disaster interference assessment module and a dynamic adjustment module; Ground stress monitoring module: monitors the stress changes of the dam foundation and surrounding rock formations through borehole stress gauges, analyzes the fluctuation of the ground stress rate over time, and determines whether there is abnormal stress concentration or release; Seismic wave monitoring and analysis module: If there is abnormal stress concentration or release, the array-type seismic monitoring sensor will analyze the abnormal changes in seismic wave velocity based on the propagation characteristics of microseisms and seismic waves in the dam area to determine whether there are local rock structure changes or hidden damage; Geological hazard interference assessment module: Construct a geological hazard interference assessment model, calculate the interference index based on the fluctuation of the rate of change of ground stress over time and the abnormal change of seismic wave velocity, and divide the interference degree into high interference degree level and low interference degree level; Dynamic adjustment module: When the interference index reaches a high interference level, the dynamic adjustment mechanism is immediately activated. According to the interference situation, the sensitivity and data collection frequency of the monitoring equipment are remotely adjusted, and the warning threshold is automatically adjusted to increase or decrease the warning sensitivity.

[0015] In the above technical solution, the technical effects and advantages provided by the present invention are: 1. The present invention uses the combined monitoring of borehole stress gauges and array-type seismic monitoring sensors to accurately identify abnormal stress changes in the dam foundation and surrounding rock formations, abnormal seismic wave velocity, and rock structure damage. By calculating the fluctuation index of the ground stress change rate and the seismic wave velocity anomaly index, a geological disaster interference assessment model is constructed, the interference degree of the monitoring data is comprehensively analyzed, and high interference and low interference levels are divided based on the interference index. When the interference index reaches a high interference level, the system immediately starts a dynamic adjustment mechanism, remotely optimizes the sensitivity of the monitoring equipment, adjusts the data acquisition frequency, and adaptively optimizes the early warning threshold to improve the monitoring system's ability to respond to sudden geological disasters.

[0016] 2. The implementation of the present invention can effectively improve the stability, reliability and accuracy of dam safety monitoring, and overcome the defects of traditional monitoring methods that are easily disturbed by geological disasters and have low early warning accuracy. In complex terrain environments, this method can achieve real-time monitoring, intelligent identification, and accurate early warning, reduce monitoring errors caused by geological disasters such as landslides, subsidence, and ground fissures, and improve the intelligence level of dam safety assessment. Through remote dynamic adjustment, the system can adaptively adjust monitoring parameters according to real-time monitoring conditions, reduce false alarms and missed alarms, and ultimately improve the long-term safety and management efficiency of water conservancy projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0018] Figure 1 The figure is a flow chart of the method of the present invention.

[0019] Figure 2 It is a system module diagram of the present invention. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Example 1, please refer to Figure 1 As shown, a water conservancy project safety risk assessment method described in this embodiment includes the following steps: S1: Monitor the stress changes of the dam foundation and surrounding rock formations through borehole stress gauges, analyze the fluctuation of the rate of change of ground stress over time, and determine whether there is abnormal stress concentration or release; S2: If there is abnormal stress concentration or release, the array-type seismic monitoring sensor will be used to analyze the abnormal changes in seismic wave velocity based on the propagation characteristics of microseisms and seismic waves in the dam area to determine whether there are local rock structure changes or hidden damage; S3: Construct a geological disaster interference assessment model, calculate the interference index according to the fluctuation of the change rate of ground stress over time and the abnormal change of seismic wave velocity, and divide the interference degree into high interference degree level and low interference degree level; S4: When the interference index reaches a high interference level, the dynamic adjustment mechanism is immediately activated. According to the interference situation, the sensitivity and data collection frequency of the monitoring equipment are remotely adjusted, and the warning threshold is automatically adjusted to increase or decrease the warning sensitivity.

[0022] In S1, borehole stress gauges are deployed at key locations of the dam foundation and surrounding rock formations (such as dam abutments, deep in the dam foundation, and near fault zones) to monitor the three-dimensional stress state. A multi-point deployment strategy is adopted to ensure the representativeness of the data and avoid local anomalies affecting the overall assessment.

[0023] High-precision borehole stress sensors are used to periodically measure the magnitude, direction and rate of change of the principal stress of the rock formation. The data is transmitted to the remote monitoring center via wireless transmission, optical fiber or LoRa communication.

[0024] The fluctuation of the rate of change of ground stress over time is analyzed to generate a ground stress change rate fluctuation index, which is used to determine whether there is abnormal stress concentration or release. The method for obtaining the ground stress change rate fluctuation index is as follows: Collect the time series of the rate of change of ground stress , the expression is: ;in: is the change in ground stress, Δt is the time interval (such as seconds, hours, days). Decompose into multiple component IMFs of different scales and extract the main oscillation modes.

[0025] Decompose the original signal by the envelope method and extract multiple intrinsic mode functions: ;in: is the ith IMF component, is the final residual, which represents the overall trend term, and N represents the number of intrinsic mode functions obtained by decomposition, that is, the number of intrinsic mode functions extracted from the original signal during the decomposition process. Set the termination condition, when the residual Stop decomposition when it becomes a monotonic function or a low-frequency trend signal.

[0026] Calculate the energy contribution of each IMF component : ; Select the IMF components with higher energy for subsequent analysis (usually remove the high-frequency components with larger noise).

[0027] Calculate the instantaneous amplitude and instantaneous frequency of each IMF component, analyze the fluctuation characteristics of the ground stress change rate, and Perform Hilbert transform to obtain its analytical signal and calculate the instantaneous amplitude , the expression is: ; is the analytic signal obtained after Hilbert transform; calculate the weighted average instantaneous amplitude , and the expression is: ; where: is the energy weight, M is the total number of instantaneous amplitudes, calculate the weighted average instantaneous frequency , and the expression is: ; in the formula, is the instantaneous frequency, and the calculation expression is: ; calculate the stress change rate fluctuation index SCRFI, and the expression is: .

[0028] Set the normal range [SCRFImin, SCRFImax] (which can be statistically based on historical data) for early warning: Normal (low risk): SCRFI ≤ SCRFImin; Attention (medium risk): SCRFImin < SCRFI ≤ SCRFImax; Abnormal (high risk): SCRFI > SCRFImax. At this time, there is stress concentration or release, and a warning signal is generated.

[0029] S2: If there is abnormal stress concentration or release, then through the array-type seismic monitoring sensors, according to the propagation characteristics of microseisms and seismic waves in the dam area, analyze the abnormal changes in seismic wave velocity to determine whether there are local rock mass structure changes or hidden damages.

[0030] Arrange array-type seismic monitoring sensors in the key areas of the dam foundation, dam shoulders, and surrounding rock masses, and adopt a three-dimensional seismic monitoring network to ensure that the data covers the entire dam area. Select high-sensitivity three-component seismometers (3C Geophone) that can monitor P-waves (longitudinal waves) and S-waves (transverse waves).

[0031] The sensors record microseism and seismic waveform data in real time at a high sampling rate (≥100Hz), including information such as amplitude, frequency, and phase. Record signals from different seismic sources such as natural earthquakes, engineering blasting, and internal microseisms of the dam body.

[0032] Calculation formula for seismic wave velocity V: ; where: d is the propagation distance between two sensors; t is the time difference for the seismic wave to reach the two sensors.

[0033] Adopt the double-difference seismic location method to eliminate the seismic source error and improve the location accuracy. Calculate the relative time delay (Time Delay) of multiple sensors through the cross-correlation method to determine the seismic source location.

[0034] Extract the first arrival times of P-waves and S-waves through waveform analysis: ; where: is the first arrival time of the P-wave, is the first arrival time of the S wave. Calculate the Poisson's ratio to infer the rock mass rupture: ; If the Poisson's ratio changes abnormally, it may indicate the existence of crack expansion or rupture inside the rock mass.

[0035] After analyzing the abnormal changes in seismic wave velocity, the seismic wave velocity anomaly index is generated to determine whether there are local rock structure changes or hidden damage. The method for obtaining the seismic wave velocity anomaly index is as follows: Assume that the seismic wave velocity time series is: ; Where: V(k) is the seismic wave velocity at the kth moment (such as the P wave velocity or S wave velocity ). Construct an additive generation sequence. To reduce randomness, perform an additive generation (AGO): ;in: ; The purpose of this step is to enhance the smoothness of the data and reduce the impact of fluctuations in a short period of time. Using the GM(1,1) model, the cumulative generated sequence is set to satisfy the differential equation: ; Where: a is the development coefficient, which indicates the trend of seismic wave velocity change; b is the gray action, which indicates the external influence of the system. Use the least squares method to estimate a and b, and based on the solved a and b, the prediction formula of the GM (1,1) model is obtained: ; Through a cumulative reduction, the predicted value of the original sequence is obtained , the expression is: ; Define the seismic wave velocity anomaly index SWVAI, the expression is: ;in: represents the actual observed seismic wave velocity at the kth moment, represents the seismic wave velocity predicted by the GM(1,1) model, is the standard deviation of historical forecast errors, and ϵ is a smoothing factor to prevent the denominator from approaching zero.

[0036] The structural state of the rock mass is determined based on the SWVAI value: SWVAI < 1 indicates that the rock mass is in normal condition and there is no significant abnormality in the seismic wave velocity; 1 ≤ SWVAI < 2 indicates that the rock mass is slightly abnormal and there may be local crack development; 2 ≤ SWVAI < 3 indicates that the rock mass is moderately abnormal and there may be rock rupture or water infiltration; SWVAI ≥ 3 indicates that the rock mass is highly abnormal and there may be large-scale rock rupture, landslide or dam foundation instability; When SWVAI ≥ 3, an automatic warning is triggered. It is recommended to: increase the monitoring frequency and collect higher density seismic wave velocity data; combine GNSS monitoring to assess whether the dam body has shifted; conduct engineering inspections to check whether there are new cracks or water seepage in the dam foundation rock layer.

[0037] S3: Construct a geological disaster interference assessment model, calculate the interference index based on the fluctuation of the rate of change of ground stress over time and the abnormal changes in seismic wave velocity, and divide the interference degree into high interference level and low interference level.

[0038] The in-situ stress change rate fluctuation index and the seismic wave velocity anomaly index are normalized so that they are both between [0, 1]. The interference index is obtained by weighted average calculation of the normalized in-situ stress change rate fluctuation index and seismic wave velocity anomaly index.

[0039] For example, the present invention may use the following formula to calculate the interference index, and the calculation expression is: ; In the formula, is the interference index, SCRFI is the fluctuation index of the ground stress change rate, and SWVAI is the seismic wave velocity anomaly index. is the weight coefficient of the geostress change rate fluctuation index and the seismic wave velocity anomaly index (which can be obtained based on experimental experience or machine learning optimization to determine the relative contribution of geostress and seismic wave velocity anomaly to the overall interference), and .

[0040] The obtained interference index is compared with the interference index reference threshold value pre-set according to historical data. If the interference index is greater than or equal to the pre-set interference index reference threshold value, it means that there may be significant geostress anomalies or rock structure damage in the dam area, and the monitoring data is seriously interfered with, requiring further analysis and early warning, and the interference degree is classified as a high interference level; if the interference index is less than the pre-set interference index reference threshold value, it means that the rock structure in the dam area is stable, the changes in geostress and seismic wave velocity are within the normal range, and the monitoring data is less interfered with, and the interference degree is classified as a low interference level.

[0041] S4: When the interference index reaches a high interference level, the dynamic adjustment mechanism is immediately activated to remotely adjust the sensitivity and data collection frequency of the monitoring equipment according to the interference situation, and automatically adjust the warning threshold to increase or decrease the warning sensitivity.

[0042] When the interference index reaches a high interference level, that is, the interference index is greater than or equal to the preset interference index reference threshold, the dynamic adjustment mechanism is immediately activated to analyze all interference index data within a fixed time period, calculate the mean and standard deviation of the interference index, and determine the interference situation; If the interference index mean is greater than or equal to the reference threshold of the interference index mean, and the interference index standard deviation is less than the reference threshold of the interference index standard deviation, it means that the interference is stable and high, and it is necessary to enhance the sensitivity of the equipment, increase the data collection frequency, reduce the warning threshold, and improve the warning sensitivity; If the interference index mean is greater than or equal to the reference threshold of the interference index mean, and the interference index standard deviation is greater than or equal to the reference threshold of the interference index standard deviation, it means that this is high-volatility interference, and it is necessary to increase the data collection frequency, keep the warning threshold unchanged, and combine manual analysis; If the interference index mean is less than the reference threshold of the interference index mean, and the interference index standard deviation is greater than or equal to the reference threshold of the interference index standard deviation, it means that this is a short-term abnormal fluctuation. The data collection frequency should be appropriately increased, and the warning threshold should not be adjusted temporarily, and monitoring should continue; If the interference index mean is less than the reference threshold of the interference index mean, and the interference index standard deviation is less than the reference threshold of the interference index standard deviation, it indicates that the interference situation is low and the current monitoring strategy is maintained without adjustment.

[0043] Remotely adjust the monitoring system according to the interference situation: Adjust sensor sensitivity: Increase or decrease the sensor's measurement accuracy and reduce noise interference.

[0044] Optimize data collection frequency: In high interference conditions, increase data collection frequency to improve real-time monitoring capabilities.

[0045] Dynamically adjust the warning threshold: If the interference index is stable and high (stable high interference), lower the warning threshold and enhance the warning sensitivity.

[0046] If the interference index fluctuates greatly (high-volatility interference), maintain the warning threshold to prevent false alarms.

[0047] In this embodiment, first, a borehole stress meter is used to monitor the changes in the ground stress of the dam foundation and the surrounding rock formations, and the fluctuation of the rate of change of ground stress over time is analyzed to determine whether there is abnormal stress concentration or release. If an abnormality is detected, the array-type seismic monitoring sensor should be further used to analyze the abnormal changes in the microseismic characteristics and seismic wave velocity in the dam area to determine whether there are local rock structure changes or hidden damage. Subsequently, a geological disaster interference assessment model is constructed, and the ground stress fluctuation index and the seismic wave velocity anomaly index are combined to calculate the interference index, and the interference degree is divided into high interference and low interference levels accordingly. When the interference index reaches the high interference level, the system immediately starts the dynamic adjustment mechanism, remotely adjusts the sensitivity of the monitoring equipment and the data acquisition frequency according to the interference situation, and automatically adjusts the warning threshold to optimize the warning sensitivity and improve the adaptability and accuracy of the monitoring system.

[0048] Example 2, please refer to Figure 2 As shown, a water conservancy project safety risk assessment system described in this embodiment includes a ground stress monitoring module, a seismic wave monitoring and analysis module, a geological disaster interference assessment module and a dynamic adjustment module; Ground stress monitoring module: monitors the stress changes of the dam foundation and surrounding rock formations through borehole stress gauges, analyzes the fluctuation of the ground stress rate over time, and determines whether there is abnormal stress concentration or release; Seismic wave monitoring and analysis module: If there is abnormal stress concentration or release, the array-type seismic monitoring sensor will analyze the abnormal changes in seismic wave velocity based on the propagation characteristics of microseisms and seismic waves in the dam area to determine whether there are local rock structure changes or hidden damage; Geological hazard interference assessment module: Construct a geological hazard interference assessment model, calculate the interference index based on the fluctuation of the rate of change of ground stress over time and the abnormal change of seismic wave velocity, and divide the interference degree into high interference degree level and low interference degree level; Dynamic adjustment module: When the interference index reaches a high interference level, the dynamic adjustment mechanism is immediately activated. According to the interference situation, the sensitivity and data collection frequency of the monitoring equipment are remotely adjusted, and the warning threshold is automatically adjusted to increase or decrease the warning sensitivity.

[0049] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A water conservancy project safety risk assessment method, characterized in that: It includes the following steps: S1: Monitor the stress changes of the dam foundation and surrounding rock strata through borehole stress gauges, analyze the fluctuation of the change rate of in-situ stress over time, and judge whether there is abnormal stress concentration or release; S2: If there is abnormal stress concentration or release, use array seismic monitoring sensors to analyze the abnormal changes in seismic wave velocity according to the propagation characteristics of microseisms and seismic waves in the dam area, and judge whether there is local rock mass structure change or hidden damage; S3: Construct a geological disaster interference assessment model, calculate the interference index based on the fluctuation of the change rate of in-situ stress over time and the abnormal changes in seismic wave velocity, and divide the interference degree into high interference degree level and low interference degree level; S4: When the interference index reaches the high interference degree level, immediately activate the dynamic adjustment mechanism, remotely adjust the sensitivity and data acquisition frequency of the monitoring equipment according to the interference situation, and automatically adjust the warning threshold to increase or decrease the warning sensitivity.

2. A water conservancy project safety risk assessment method according to claim 1, characterized in that: In S1, analyze the fluctuation of the change rate of in-situ stress over time to generate an in-situ stress change rate fluctuation index. The method for obtaining the in-situ stress change rate fluctuation index is as follows: Collect the time series of the rate of change of ground stress , the expression is: ;in: is the change of ground stress, Δt is the time interval, and the ground stress change rate series Decompose into multiple component IMFs of different scales, decompose the original signal by the envelope method, and extract multiple intrinsic mode functions: ;in: is the ith IMF component, is the final residual, N represents the number of intrinsic mode functions obtained by decomposition, that is, the number of intrinsic mode functions extracted from the original signal during the decomposition process, and the termination condition is set. Stop decomposition when it becomes a monotonic function or a low-frequency trend signal; Calculate the energy contribution of each IMF component : ; Calculate the instantaneous amplitude and instantaneous frequency of each IMF component, analyze the fluctuation characteristics of the ground stress change rate, and Perform Hilbert transform to obtain its analytical signal and calculate the instantaneous amplitude , the expression is: ; is the analytical signal obtained after Hilbert transform; calculate the weighted average instantaneous amplitude , the expression is: ;in: is the energy weight, M is the total instantaneous amplitude, and the weighted average instantaneous frequency is calculated , the expression is: ; In the formula, is the instantaneous frequency, and the calculation expression is: ; Calculate the geostress change rate fluctuation index SCRFI, the expression is: .

3. A water conservancy project safety risk assessment method according to claim 2, characterized in that: Set the normal range [SCRFImin, SCRFImax] for early warning: Low risk: SCRFI ≤ SCRFImin; Medium risk: SCRFImin < SCRFI ≤ SCRFImax; High risk: SCRFI > SCRFImax. At this time, there is stress concentration or release, and a warning signal is generated.

4. A water conservancy project safety risk assessment method according to claim 3, characterized in that: After analyzing the abnormal changes in seismic wave velocity, generate a seismic wave velocity abnormal index. The method for obtaining the seismic wave velocity abnormal index is as follows: Assume that the seismic wave velocity time series is: ; Where: V(k) is the seismic wave velocity at the kth moment. Construct a cumulative generation sequence and perform a cumulative generation: ;in: ; Use the GM(1,1) model to set the cumulative generated sequence to satisfy the differential equation: ; Where: a is the development coefficient, which represents the trend of seismic wave velocity change; b is the gray action, which represents the external influence of the system. The least squares method is used to estimate a and b. Based on the solved a and b, the prediction formula of the GM (1,1) model is obtained: ; Through a cumulative reduction, the predicted value of the original sequence is obtained , the expression is: ; Define the seismic wave velocity anomaly index SWVAI, the expression is: ;in: represents the actual observed seismic wave velocity at the kth moment, represents the seismic wave velocity predicted by the GM(1,1) model, is the standard deviation of historical forecast errors, and ϵ is the smoothing factor.

5. A water conservancy project safety risk assessment method according to claim 4, characterized in that: Judge the rock mass structure state according to the SWVAI value: SWVAI < 1 indicates that the rock mass state is normal and there is no significant abnormality in seismic wave velocity; 1 ≤ SWVAI < 2 indicates that the rock mass state is slightly abnormal and there is local crack development; 2 ≤ SWVAI < 3 indicates that the rock mass state is moderately abnormal and there is rock mass rupture or increased water penetration; SWVAI ≥ 3 indicates that the rock mass state is highly abnormal and there is large-scale rock mass rupture, landslide or dam foundation instability; When SWVAI ≥ 3, trigger an automatic warning, increase the monitoring frequency, and collect seismic wave velocity data with higher density.

6. A water conservancy project safety risk assessment method according to claim 5, characterized in that: In S3, construct a geological disaster interference assessment model, calculate the interference index based on the fluctuation of the change rate of in-situ stress over time and the abnormal changes in seismic wave velocity, and divide the interference degree into high interference degree level and low interference degree level; Normalize the in-situ stress change rate fluctuation index and the seismic wave velocity abnormal index so that they are both within [0, 1], and obtain the interference index by weighted average calculation of the normalized in-situ stress change rate fluctuation index and the seismic wave velocity abnormal index.

7. A water conservancy project safety risk assessment method according to claim 6, characterized in that: The obtained interference index is compared with the interference index reference threshold value pre-set according to historical data. If the interference index is greater than or equal to the pre-set interference index reference threshold value, it means that there is significant geostress anomaly or rock structure damage in the dam area, and the monitoring data is seriously interfered with, requiring further analysis and early warning, and the interference degree is classified as a high interference level; if the interference index is less than the pre-set interference index reference threshold value, it means that the rock structure in the dam area is stable, the changes in geostress and seismic wave velocity are within the normal range, and the monitoring data is less interfered with, and the interference degree is classified as a low interference level.

8. A water conservancy project safety risk assessment method according to claim 7, characterized in that: In S4, when the interference index reaches the high interference level, the dynamic adjustment mechanism is immediately activated to remotely adjust the sensitivity and data collection frequency of the monitoring equipment according to the interference situation, and automatically adjust the warning threshold to increase or decrease the warning sensitivity; When the interference index reaches a high interference level, that is, the interference index is greater than or equal to the preset interference index reference threshold, the dynamic adjustment mechanism is immediately activated to analyze all interference index data within a fixed time period, calculate the mean and standard deviation of the interference index, and determine the interference situation; If the interference index mean is greater than or equal to the reference threshold of the interference index mean, and the interference index standard deviation is less than the reference threshold of the interference index standard deviation, it means that the situation is stable and high interference is needed. It is necessary to enhance the sensitivity of the equipment, increase the frequency of data collection, reduce the warning threshold, and improve the warning sensitivity. If the interference index mean is greater than or equal to the reference threshold of the interference index mean, and the interference index standard deviation is greater than or equal to the reference threshold of the interference index standard deviation, it indicates that this is a high-interference situation with volatility, and the data collection frequency needs to be increased to keep the warning threshold unchanged; If the interference index mean is less than the reference threshold of the interference index mean, and the interference index standard deviation is greater than or equal to the reference threshold of the interference index standard deviation, it indicates that this is a short-term abnormal fluctuation. Increase the data collection frequency, do not adjust the warning threshold for the time being, and continue monitoring; If the interference index mean is less than the reference threshold of the interference index mean, and the interference index standard deviation is less than the reference threshold of the interference index standard deviation, it indicates that the interference situation is low and the current monitoring strategy is maintained without adjustment.

9. A water conservancy project safety risk assessment system, used to implement a water conservancy project safety risk assessment method according to any one of claims 1 to 8, characterized in that: It includes ground stress monitoring module, seismic wave monitoring and analysis module, geological disaster interference assessment module and dynamic adjustment module; Ground stress monitoring module: monitors the stress changes of the dam foundation and surrounding rock formations through borehole stress gauges, analyzes the fluctuation of the ground stress rate over time, and determines whether there is abnormal stress concentration or release; Seismic wave monitoring and analysis module: If there is abnormal stress concentration or release, the array-type seismic monitoring sensor will analyze the abnormal changes in seismic wave velocity based on the propagation characteristics of microseisms and seismic waves in the dam area to determine whether there are local rock structure changes or hidden damage; Geological hazard interference assessment module: Construct a geological hazard interference assessment model, calculate the interference index based on the fluctuation of the rate of change of ground stress over time and the abnormal change of seismic wave velocity, and divide the interference degree into high interference degree level and low interference degree level; Dynamic adjustment module: When the interference index reaches a high interference level, the dynamic adjustment mechanism is immediately activated. According to the interference situation, the sensitivity and data collection frequency of the monitoring equipment are remotely adjusted, and the warning threshold is automatically adjusted to increase or decrease the warning sensitivity.

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